Recent Advances in RecBole: Extensions with more Practical Considerations
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Abstract (arXiv)
RecBole has recently attracted increasing attention from the research community. As the increase of the number of users, we have received a number of suggestions and update requests. This motivates us to make some significant improvements on our library, so as to meet the user requirements and contribute to the research community. In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole. In general, we focus on the flexibility and efficiency of RecBole in the past few months. More specifically, we have four development targets: (1) more flexible data processing, (2) more efficient model training, (3) more reproducible configurations, and (4) more comprehensive user documentation. Readers can download the above updates at: https://github.com/RUCAIBox/RecBole.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Nov 2022.
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Citing papers per year: 2023: 3; 2024: 1.
4 papers.
- 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
- 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systemscited by 116
- 2024KG4RecEval: Does Knowledge Graph Really Matter for Recommender Systems?cited by 1
- 2023Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?cited by 0
- 2024KG4RecEval: Does Knowledge Graph Really Matter for Recommender Systems?4 Apr 2024
- 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems13 Oct 2023
- 2023Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?16 Aug 2023
- 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach11 May 2023